AI Job Risk in Australia
Australia is best read as a country where urban service work and strongly field-dependent work sit side by side. If you look only at the speed of AI adoption, it becomes easy to miss the resilience created by regional variation and on-the-ground constraints.
Average AI Risk
42.76 / 100
Jobs Analyzed
204
How to read this page in practice
The notes below explain how to interpret the country score, what kinds of sector mix usually raise or lower it, and what this comparison can and cannot tell you.
How to Read This Country
A better reading of Australia starts with how a large service economy and dispersed field work coexist inside the same labor market. Australia cannot be reduced to a single industrial pattern, so the more useful approach is to look at both the industries that carry weight nationally and the kinds of work that remain tied to location, local conditions, and face-to-face judgment.
What Drives the Score
Australia combines large urban service sectors with resource-related and field-based work spread across a wide geography. Information-heavy and repeatable tasks are easier to automate, but work shaped by distance, local conditions, safety requirements, and real-world coordination tends to change more slowly.
What Holds Up Better
The work that remains strongest here is work that changes with place. In a country where uniform operations are harder to impose across every region, roles built on exception handling, site judgment, and local coordination keep more of their value.
What This Page Does Not Claim
This page shows a national average, not a claim that digital roles in major cities and field roles in remote regions move at the same speed. Read the score together with industry mix, geography, and the gap between centrally organized work and work that stays local.
Jobs Most At Risk from AI
This table is a current snapshot of the jobs that appear on the higher-risk side within this country profile. It is useful as a directional comparison, not as a permanent national ranking.
| Rank | Job | Risk Score |
|---|---|---|
| 1 | Data Entry Clerk | 81 |
| 2 | Retail Cashier | 78 |
| 3 | Bookkeeper | 77 |
| 4 | Truck Driver | 77 |
| 5 | Software Tester | 77 |
| 6 | Accounting Clerk | 76 |
| 7 | Data Analyst | 76 |
| 8 | Receptionist | 74 |
| 9 | Insurance Underwriter | 73 |
| 10 | Civil Drafter | 73 |
| 11 | Taxi Driver | 71 |
| 12 | Travel Agent | 70 |
| 13 | Bank Teller | 69 |
| 14 | QA Engineer | 69 |
| 15 | Tax Preparer | 68 |
| 16 | Mobile App Developer | 68 |
| 17 | Train Operator | 67 |
| 18 | System Administrator | 67 |
| 19 | Software Engineer | 66 |
| 20 | Surveying Technician | 64 |
Jobs Safest from AI
This table shows the jobs that currently appear on the lower-risk side within this country profile. Read it as a structural comparison of work, not as a guarantee that these roles will stay unchanged.
| Rank | Job | Risk Score |
|---|---|---|
| 1 | Surgeon | 10 |
| 2 | Therapist | 11 |
| 3 | Plumber | 11 |
| 4 | Psychologist | 12 |
| 5 | Electrician | 12 |
| 6 | Paramedic | 14 |
| 7 | Nurse | 15 |
| 8 | Dentist | 15 |
| 9 | Psychiatrist | 16 |
| 10 | School Counselor | 16 |
| 11 | Athletic Coach | 16 |
| 12 | Veterinarian | 17 |
| 13 | Professor | 18 |
| 14 | Doctor | 19 |
| 15 | Social Worker | 20 |
| 16 | Air Traffic Controller | 20 |
| 17 | Machine Learning Engineer | 20 |
| 18 | Fitness Trainer | 20 |
| 19 | Elevator Technician | 21 |
| 20 | Teacher | 22 |
Industry Risk
This table compares the industries that shape the country score today. It is most useful for seeing which parts of the economy pull the average up or down.
| Industry | Industry Average Risk Score |
|---|---|
| Retail | 61.5 |
| Finance | 59.47 |
| Technology | 52.22 |
| Transportation | 45.3 |
| Agriculture | 42.25 |
| Energy | 37.33 |
| Hospitality | 35.62 |
| Construction | 34.33 |
| Education | 31.67 |
| Science | 31.33 |
| Healthcare | 26.2 |